Simultaneous port number and location optimization of mold gates‐vents using in‐house coded stochastic multi‐objective optimization algorithm

Abstract

AbstractThis research introduces multi‐objective stochastic optimization (MOSO) and non‐dominated sorting differential evolution (NSDE) in‐house coded algorithms for enhancing the optimization of the resin transfer molding (RTM) process during the mold‐fill phase for composite parts. Glass fiber‐vinyl ester‐based automotive bonnet and carbon fiber‐RTM6‐based aircraft wing flap parts were used as the case studies. Initially, the NSDE algorithm was developed for the simultaneous optimization of dry‐spot content and mold‐fill time by changing the locations of gates and vents with pre‐fixed port numbers. Then, the MOSO algorithm was designed for the concurrent optimization of the dry‐spot content, mold‐fill time and total number of ports by changing both the numbers and locations of gates and vents. The effect of race‐tracking was also investigated using higher permeability values at the composite part‐cut edges. When compared, the MOSO algorithm predicted less dry‐spot content, number of ports, mold‐fill time and uniform resin flow‐front progressions with lesser functional evaluations and computational time than the NSDE algorithm.Highlights The non‐dominated sorting differential evolution (NSDE) and multi‐objective stochastic optimization (MOSO) algorithms were developed for the optimization of the mold fill phase of resin transfer molded composite parts. The development of the NSDE algorithm aimed to concurrently optimize the dry‐spot content and mold‐fill time by changing the locations of gates and vents with pre‐fixed port numbers. The MOSO algorithm was designed to concurrently optimize dry‐spot content, mold‐fill time, and the total number of ports by varying both the numbers and locations of gates and vents. The MOSO algorithm predicted better‐automated mold‐fill phase optimalities for the resin transfer molded composite parts compared to the NSDE algorithm.